aff75303759349db45579315630cb17e9370f86f hiram Fri Jul 5 16:07:27 2024 -0700 now with assembly exist signal and including all RefSeq potential assemblies refs #32897 diff --git src/hg/hubApi/genomePriority.py src/hg/hubApi/genomePriority.py index 7f22cad..addcb207 100755 --- src/hg/hubApi/genomePriority.py +++ src/hg/hubApi/genomePriority.py @@ -1,485 +1,655 @@ #!/cluster/software/bin/python3 import subprocess import locale import sys import re import os import csv import requests from io import StringIO # special top priorities topPriorities = { 'hg38': 1, 'mm39': 2, 'hs1': 3, } ### key will be dbDb name, value will be priority number allPriorities = {} priorityCounter = len(topPriorities) + 1 #################################################################### def set_utf8_encoding(): """ Set UTF-8 encoding for stdin, stdout, and stderr in Python. """ if sys.stdout.encoding != 'utf-8': sys.stdout = open(sys.stdout.fileno(), mode='w', encoding='utf-8', buffering=1) if sys.stderr.encoding != 'utf-8': sys.stderr = open(sys.stderr.fileno(), mode='w', encoding='utf-8', buffering=1) #################################################################### def dbDbData(): # Run the MySQL command and capture the output as bytes result = subprocess.run( ["hgsql", "-hgenome-centdb", "-N", "-e", "SELECT name,scientificName,organism,taxId,sourceName,description FROM dbDb WHERE active=1;", "hgcentral"], stdout=subprocess.PIPE, stderr=subprocess.PIPE ) if result.returncode != 0: print(f"Error executing MySQL command: {result.stderr.decode('utf-8')}") exit(1) # Decode the output from bytes to string using utf-8 return result.stdout.decode('latin-1') #################################################################### +def readCommonNames(ncbiType): + commonNames = {} + + filePath = "/hive/data/outside/ncbi/genomes/reports/" + ncbiType + "/allAssemblies.commonNames.tsv" + + with open(filePath, 'r', encoding='utf-8') as file: + reader = csv.reader(file, delimiter='\t') + for row in reader: + commonNames[row[1]] = row[3] + + return commonNames + +#################################################################### +""" + header definitions from assembly_summary_refseq.txt + + 1 #assembly_accession 20 ftp_path + 2 bioproject 21 excluded_from_refseq + 3 biosample 22 relation_to_type_material + 4 wgs_master 23 asm_not_live_date + 5 refseq_category 24 assembly_type + 6 taxid 25 group + 7 species_taxid 26 genome_size + 8 organism_name 27 genome_size_ungapped + 9 infraspecific_name 28 gc_percent + 10 isolate 29 replicon_count + 11 version_status 30 scaffold_count + 12 assembly_level 31 contig_count + 13 release_type 32 annotation_provider + 14 genome_rep 33 annotation_name + 15 seq_rel_date 34 annotation_date + 16 asm_name 35 total_gene_count + 17 asm_submitter 36 protein_coding_gene_count + 18 gbrs_paired_asm 37 non_coding_gene_count + 19 paired_asm_comp 38 pubmed_id + +Would be good to verify this in the readAsmSummary to make sure it +hasn't changed. + + 2175 archaea + 360585 bacteria + 607 fungi + 414 invertebrate + 184 plant + 96 protozoa + 231 vertebrate_mammalian + 405 vertebrate_other + 14992 viral + + +""" + +def readAsmSummary(suffix, prioExists, comNames): + # read one of the NCBI files from + # /hive/data/outside/ncbi/genomes/reports/assembly_summary_{suffix} + # Initialize a list to hold the dictionaries + dataList = [] + keys = [ +"vertebrate_mammalian", +"vertebrate_other", +"invertebrate", +"plant", +"fungi", +"protozoa", +"viral", +"bacteria", +"archaea", + ] + values = [ +'1', +'2', +'3', +'4', +'5', +'6', +'7', +'8', +'0', + ] + cladePrio = dict(zip(keys, values)) + + filePath = "/hive/data/outside/ncbi/genomes/reports/assembly_summary_" + suffix + + with open(filePath, 'r', encoding='utf-8') as file: + reader = csv.reader(file, delimiter='\t') + for row in reader: + if len(row) < 1: + continue + if row[0].startswith('#'): + continue + if row[0] in prioExists: + continue + if len(row) != 38: + print(f"ERROR: incorrect number of fields in {file}") + sys.exit(1) + gcAccession = row[0] + strain = re.sub(r'breed=', '', row[8]) + s0 = re.sub(r'cultivar=', '', strain) + strain = re.sub(r'ecotype=', '', s0) + s0 = re.sub(r'strain=', '', strain) + strain = re.sub(r'na', '', s0) + year = re.sub(r'/.*', '', row[14]) + asmSubmitter = row[16] + asmType = row[23] +# commonName = row[7] + commonName = "n/a" + if gcAccession in comNames: + commonName = comNames[gcAccession] + dataDict = { + "gcAccession": gcAccession, + "asmName": row[15], + "scientificName": row[7], + "commonName": commonName, + "taxId": row[5], + "clade": row[24], # almost like GenArk clades + "other": asmSubmitter + " " + strain + " " + asmType + " " + year, + "sortOrder": cladePrio[row[24]] + } + + utf8Encoded= {k: v.encode('utf-8', 'ignore').decode('utf-8') if isinstance(v, str) else v for k, v in dataDict.items()} + # Append the dictionary to the list + dataList.append(utf8Encoded) + + return sorted(dataList, key=lambda x: x['sortOrder']) + +#################################################################### ### given a URL to hgdownload file: /hubs/UCSC_GI.assemblyHubList.txt def readGenArkData(url): # Initialize a list to hold the dictionaries dataList = [] response = requests.get(url) response.raise_for_status() fileContent = response.text fileIo = StringIO(fileContent) reader = csv.reader(fileIo, delimiter='\t') for row in reader: if row and row[0].startswith('#'): continue dataDict = { "gcAccession": row[0], "asmName": row[1], "scientificName": row[2], "commonName": row[3], "taxId": row[4], "clade": re.sub(r'\(L\)$', '', row[5]), } utf8Encoded= {k: v.encode('utf-8', 'ignore').decode('utf-8') if isinstance(v, str) else v for k, v in dataDict.items()} # Append the dictionary to the list dataList.append(utf8Encoded) # reset the list so that accessions such as GCF_000001405.40 # come before GCF_000001405.39 dataList.reverse() return dataList #################################################################### def dbDbCladeList(filePath): returnList = {} with open(filePath, 'r') as file: reader = csv.reader(file, delimiter='\t') for row in reader: if len(row) < 1: continue if row[0].startswith('#'): continue returnList[row[0]] = row[1] return returnList #################################################################### def extractClade(clade, genArkData): tmpList = {} for item in genArkData: if clade != item['clade']: continue tmpList[item['gcAccession']] = item['commonName'] # return sorted list on the common name, case insensitive returnList = dict(sorted(tmpList.items(), key=lambda item:item[1].lower())) return returnList #################################################################### # Define a key function for sorting by the first word, case insensitive def getFirstWordCaseInsensitive(row): firstWord = row.split('\t')[0] # Extract the first word return firstWord.lower() # Convert to lowercase for case-insensitive sorting #################################################################### def processDbDbData(data, clades): # Initialize a list to hold the dictionaries dataList = [] # Split the data into lines (rows) rows = data.strip().split('\n') # reverse the rows so that names such as hg19 come before hg18 sortedRows = sorted(rows, key=getFirstWordCaseInsensitive, reverse=True) for row in sortedRows: # Split each row into columns columns = row.split('\t') clade = clades.get(columns[0], "n/a") # corresponds with the SELECT statement # name,scientificName,organism,taxId,sourceName,description # Create a dictionary for each row dataDict = { "name": columns[0], "scientificName": columns[1], "organism": columns[2], "taxId": columns[3], "sourceName": columns[4], "description": columns[5], "clade": clade, } utf8Encoded= {k: v.encode('utf-8', 'ignore').decode('utf-8') if isinstance(v, str) else v for k, v in dataDict.items()} # Append the dictionary to the list dataList.append(utf8Encoded) return dataList #################################################################### # Function to remove non-alphanumeric characters def removeNonAlphanumeric(s): # Ensure string type if isinstance(s, str): reSub = re.sub(r'[^a-zA-Z0-9_]', ' ', s).strip() return re.sub(r'\s+', ' ', reSub) else: return s # Return as-is for non-string types #################################################################### def eliminateDupWords(s): # Split the sentence into words words = s.split() # Initialize a set to keep track of unique words encountered seenWords = set() # List to store the words with duplicates removed resultWords = [] for word in words: # Convert word to lowercase for case-insensitive comparison lowerWord = word.lower() # Check if the lowercase version of the word has been seen before if lowerWord not in seenWords: # If not seen, add it to the result list and mark as seen resultWords.append(word) seenWords.add(lowerWord) # Join the words back into a single string return ' '.join(resultWords) #################################################################### def establishPriorities(dbDb, genArk): global topPriorities global allPriorities global priorityCounter totalItemCount = 0 expectedTotal = len(dbDb) + len(genArk) print(f"### expected total: {expectedTotal:4} = {len(dbDb):4} dbDb genomes + {len(genArk):4} genArk genomes") # first priority are the specific manually selected top items itemCount = 0 for name, priority in topPriorities.items(): allPriorities[name] = priority itemCount += 1 totalItemCount += itemCount print(f"{totalItemCount:4} - total\ttopPriorities count: {itemCount:4}") primateList = extractClade('primates', genArk) mammalList = extractClade('mammals', genArk) versionScan = {} # key is dbDb name without number version extension, # value is highest version number seen for this bare # name highestVersion = {} # key is dbDb name without number version extension, # value is the full dbDb name for the highest version # of this dbDb name allDbDbNames = {} # key is the full dbDb name, value is its version itemCount = 0 # scanning the dbDb entries, figure out the highest version number # of each name for item in dbDb: dbDbName = item['name'] splitMatch = re.match("([a-zA-Z]+)(\d+)", dbDbName) if splitMatch: allDbDbNames[dbDbName] = splitMatch.group(2) itemCount += 1 if splitMatch.group(1) in versionScan: if splitMatch.group(2) > versionScan[splitMatch.group(1)]: versionScan[splitMatch.group(1)] = splitMatch.group(2) highestVersion[splitMatch.group(1)] = dbDbName else: versionScan[splitMatch.group(1)] = splitMatch.group(2) highestVersion[splitMatch.group(1)] = dbDbName else: print("### dbDb name does not split: ", dbDbName) allDbDbNames[dbDbName] = 0 itemCount += 1 dbDbLen = len(dbDb) # second priority are the highest versioned database primates # but not homo sapiens since we already have hg38 in topPriorities itemCount = 0 sortByValue = sorted(versionScan.items(), key=lambda x: x[1], reverse=True) for key in sortByValue: highVersion = highestVersion[key[0]] if highVersion not in allPriorities: # find the element in the dbDb list that matches this highVersion name highDict = next((d for d in dbDb if d.get('name') == highVersion), None) if highDict['clade'] == "primates": if highDict['scientificName'].lower() != "homo sapiens": allPriorities[highVersion] = priorityCounter priorityCounter += 1 itemCount += 1 totalItemCount += itemCount print(f"{totalItemCount:4} - total\tdbDb highest version primates count: {itemCount:4}") itemCount = 0 # and now the GenArk GCF/RefSeq homo sapiens should be lined up here next for item in genArk: gcAccession = item['gcAccession'] if not gcAccession.startswith("GCF_"): continue if gcAccession not in allPriorities: sciName = item['scientificName'] if sciName.lower() == "homo sapiens": allPriorities[gcAccession] = priorityCounter priorityCounter += 1 itemCount += 1 totalItemCount += itemCount print(f"{totalItemCount:4} - total\tgenArk GCF homo sapiens count: {itemCount:4}") itemCount = 0 # and now the GenArk GCA/GenBank homo sapiens should be lined up here next # GCA/GenBank second for item in genArk: gcAccession = item['gcAccession'] if not gcAccession.startswith("GCA_"): continue if gcAccession not in allPriorities: sciName = item['scientificName'] if sciName.lower() == "homo sapiens": allPriorities[gcAccession] = priorityCounter priorityCounter += 1 itemCount += 1 totalItemCount += itemCount print(f"{totalItemCount:4} - total\tgenArk GCA homo sapiens count: {itemCount:4}") itemCount = 0 # the primates, GCF/RefSeq first for asmId, commonName in primateList.items(): gcAcc = asmId.split('_')[0] + "_" + asmId.split('_')[1] if not gcAcc.startswith("GCF_"): continue if gcAcc not in allPriorities: allPriorities[gcAcc] = priorityCounter priorityCounter += 1 itemCount += 1 totalItemCount += itemCount print(f"{totalItemCount:4} - total\tgenArk GCF primates count: {itemCount:4}") itemCount = 0 # and the GCA/GenBank primates for asmId, commonName in primateList.items(): gcAcc = asmId.split('_')[0] + "_" + asmId.split('_')[1] if not gcAcc.startswith("GCA_"): continue if gcAcc not in allPriorities: allPriorities[gcAcc] = priorityCounter priorityCounter += 1 itemCount += 1 totalItemCount += itemCount print(f"{totalItemCount:4} - total\tgenArk GCA primates count: {itemCount:4}") # next are the highest versioned database mammals itemCount = 0 sortByValue = sorted(versionScan.items(), key=lambda x: x[1], reverse=True) for key in sortByValue: highVersion = highestVersion[key[0]] if highVersion not in allPriorities: # find the element in the dbDb list that matches this highVersion name highDict = next((d for d in dbDb if d.get('name') == highVersion), None) if highDict['clade'] == "mammals": allPriorities[highVersion] = priorityCounter priorityCounter += 1 itemCount += 1 totalItemCount += itemCount print(f"{totalItemCount:4} - total\tdbDb highest version mammals count: {itemCount:4}") itemCount = 0 # the mammals, GCF/RefSeq first for asmId, commonName in mammalList.items(): gcAcc = asmId.split('_')[0] + "_" + asmId.split('_')[1] if not gcAcc.startswith("GCF_"): continue if gcAcc not in allPriorities: allPriorities[gcAcc] = priorityCounter priorityCounter += 1 itemCount += 1 totalItemCount += itemCount print(f"{totalItemCount:4} - total\tgenArk GCF mammals count: {itemCount:4}") itemCount = 0 # and the GCA/GenBank mammals for asmId, commonName in mammalList.items(): gcAcc = asmId.split('_')[0] + "_" + asmId.split('_')[1] if not gcAcc.startswith("GCA_"): continue if gcAcc not in allPriorities: allPriorities[gcAcc] = priorityCounter priorityCounter += 1 itemCount += 1 totalItemCount += itemCount print(f"{totalItemCount:4} - total\tgenArk GCA mammals count: {itemCount:4}") itemCount = 0 # the rest of the highest versions of each unique dbDb name sortByValue = sorted(versionScan.items(), key=lambda x: x[1], reverse=True) for key in sortByValue: highVersion = highestVersion[key[0]] if highVersion not in allPriorities: allPriorities[highVersion] = priorityCounter priorityCounter += 1 itemCount += 1 totalItemCount += itemCount print(f"{totalItemCount:4} - total\tdbDb highest versions count: {itemCount:4}") itemCount = 0 # GCF RefSeq from GenArk next priority for item in genArk: gcAccession = item['gcAccession'] if not gcAccession.startswith("GCF_"): continue if gcAccession not in allPriorities: allPriorities[gcAccession] = priorityCounter priorityCounter += 1 itemCount += 1 totalItemCount += itemCount print(f"{totalItemCount:4} - total\tgenArk GCF count: {itemCount:4}") itemCount = 0 # GCA GenBank from GenArk next priority for item in genArk: gcAccession = item['gcAccession'] if not gcAccession.startswith("GCA_"): continue if gcAccession not in allPriorities: allPriorities[gcAccession] = priorityCounter priorityCounter += 1 itemCount += 1 totalItemCount += itemCount print(f"{totalItemCount:4} - total\tgenArk GCA count: {itemCount:4}") itemCount = 0 # finally the rest of the database genomes names for dbName in sorted(allDbDbNames): if dbName not in allPriorities: allPriorities[dbName] = priorityCounter priorityCounter += 1 itemCount += 1 totalItemCount += itemCount print(f"{totalItemCount:4} - total\tthe rest of dbDb count: {itemCount:4}") #################################################################### """ table load procedure: hgsql -e 'DROP TABLE IF EXISTS genomePriority;' hgcentraltest hgsql hgcentraltest < genomePriority.sql hgsql -e 'LOAD DATA LOCAL INFILE "genomePriority.tsv" INTO TABLE genomePriority;' hgcentraltest hgsql -e 'ALTER TABLE genomePriority ADD FULLTEXT INDEX gdIx (name, commonName, scientificName, description);' hgcentraltest """ #################################################################### #################################################################### def main(): global priorityCounter global allPriorities if len(sys.argv) != 2: print("genomePriority.py - prepare genomePriority.tsv file from") print(" dbDb.hgcentral and UCSC_GI.assemblyHubList.txt file.\n") print("Usage: genomePriority.py dbDb.name.clade.tsv\n") print("the dbDb.name.clade.tsv file is a manually curated file to relate") print(" UCSC database names to GenArk clades, in source tree hubApi/") print("This script is going to read the dbDb.hgcentral table, and the file") print(" UCSC_GI.assemblyHubList.txt from hgdownload.") print("Writing an output file genomePriority.tsv to be loaded into") print(" genomePriority.hgcentral. See notes in this script for load procedure.") sys.exit(-1) dbDbNameCladeFile = sys.argv[1] # Ensure stdout and stderr use UTF-8 encoding set_utf8_encoding() # the correspondence of dbDb names to GenArk clade categories dbDbClades = dbDbCladeList(dbDbNameCladeFile) # Get the dbDb.hgcentral table data rawData = dbDbData() dbDbItems = processDbDbData(rawData, dbDbClades) # read the GenArk data from hgdownload into a list of dictionaries genArkUrl = "https://hgdownload.soe.ucsc.edu/hubs/UCSC_GI.assemblyHubList.txt" genArkItems = readGenArkData(genArkUrl) establishPriorities(dbDbItems, genArkItems) + refSeqCommonNames = readCommonNames("refseq") + print("# refseq common names: ", len(refSeqCommonNames)) + + refSeqList = readAsmSummary("refseq.txt", allPriorities, refSeqCommonNames) + + print("# refSeq assemblies: ", len(refSeqList)) + outFile = "genomePriority.tsv" fileOut = open(outFile, 'w') + totalItemCount = 0 itemCount = 0 # Print the dbDb data for entry in dbDbItems: dbDbName = entry['name'] if dbDbName in allPriorities: priority = allPriorities[dbDbName] else: print("no priority for ", dbDbName) clade = entry['clade'] - descr = f"{entry['sourceName']} {clade} {entry['taxId']} {entry['description']}\n" + descr = f"{entry['sourceName']} {clade} {entry['description']}\n" description = re.sub(r'\s+', ' ', descr).strip() - outLine =f"{entry['name']}\t{priority}\t{entry['organism']}\t{entry['scientificName']}\t{entry['taxId']}\t{description}\n" + outLine =f"{entry['name']}\t{priority}\t{entry['organism']}\t{entry['scientificName']}\t{entry['taxId']}\t{description}\t1\n" fileOut.write(outLine) itemCount += 1 + totalItemCount += itemCount + print(f"{totalItemCount:4} - total\tdbDb count: {itemCount:4}") + itemCount = 0 # Print the GenArk data for entry in genArkItems: gcAccession = entry['gcAccession'] if gcAccession in allPriorities: priority = allPriorities[gcAccession] else: print("no priority for ", gcAccession) cleanName = removeNonAlphanumeric(entry['commonName']) clade = entry['clade'] - descr = f"{entry['asmName']} {clade} {entry['taxId']}\n" + descr = f"{entry['asmName']} {clade}" + description = re.sub(r'\s+', ' ', descr).strip() + outLine = f"{entry['gcAccession']}\t{priority}\t{entry['commonName'].encode('ascii', 'ignore').decode('ascii')}\t{entry['scientificName']}\t{entry['taxId']}\t{description}\t1\n" + fileOut.write(outLine) + itemCount += 1 + + totalItemCount += itemCount + print(f"{totalItemCount:4} - total\tgenArk count: {itemCount:4}") + + itemCount = 0 + incrementPriority = len(allPriorities) + print("# incrementing priorities from: ", incrementPriority) + # Print the dbDb data + for entry in refSeqList: + gcAccession = entry['gcAccession'] + commonName = entry['commonName'] + scientificName = entry['scientificName'] + descr = f"{entry['other']} {entry['clade']}" description = re.sub(r'\s+', ' ', descr).strip() - outLine = f"{entry['gcAccession']}\t{priority}\t{entry['commonName'].encode('ascii', 'ignore').decode('ascii')}\t{entry['scientificName']}\t{entry['taxId']}\t{description}\n" + outLine = f"{entry['gcAccession']}\t{incrementPriority}\t{entry['commonName'].encode('ascii', 'ignore').decode('ascii')}\t{entry['scientificName']}\t{entry['taxId']}\t{description.encode('ascii', 'ignore').decode('ascii')}\t0\n" fileOut.write(outLine) + incrementPriority += 1 itemCount += 1 + totalItemCount += itemCount + print(f"{totalItemCount:4} - total\trefSeq count: {itemCount:4}") + +# def removeNonAlphanumeric(s): + fileOut.close() if __name__ == "__main__": main() + +""" + "gcAccession": row[0], + "asmName": row[15], + "scientificName": row[7], + "commonName": row[3], + "taxId": row[5], + "clade": row[24], # almost like GenArk clades + "other": asmSubmitter + " " + strain + " " + asmType, +"""